At a Glance
- Tasks: Lead AI development, optimise ML workflows, and code in Python for innovative solutions.
- Company: Join J.P. Morgan, a global leader in financial services with a commitment to diversity and inclusion.
- Benefits: Enjoy a collaborative culture, career growth opportunities, and the chance to work on cutting-edge technology.
- Why this job: Shape the future of intelligent testing while working with top-tier professionals in a dynamic environment.
- Qualifications: MS/PhD in Computer Science or related field; strong Python skills and ML experience required.
- Other info: Flexible work arrangements and a focus on employee well-being are part of our inclusive workplace.
The predicted salary is between 48000 - 72000 £ per year.
We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. As a Lead Software Engineer at JPMorgan Chase within the AI and Machine Learning Data Platform Team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives.
The test engineering team is at the forefront of innovation, developing intelligent agents powered by top foundational models to enhance the development and testing experience for our teams and partners. We build solutions that automate quality workflows, accelerate debugging, and enable smarter decision-making across SDLC. Join us in shaping the future of intelligent testing through cutting-edge AI and model-driven engineering.
Job responsibilities:
- Serves as a subject matter expert on a wide range of ML techniques and optimizations.
- Provides in-depth knowledge of ML algorithms, frameworks, and techniques.
- Enhances ML workflows through advanced proficiency in large language models (LLMs) and related techniques.
- Conducts experiments using latest ML technologies, analyzing results, tuning models.
- Has hands-on coding to bring the experimental results into production solutions by collaborating with the engineering team.
- Owns end-to-end code development in Python for both proof of concept/experimentation and production-ready solutions.
- Optimizes system accuracy and performance by identifying and resolving inefficiencies and bottlenecks.
- Collaborates with product and engineering teams to deliver tailored, science and technology-driven solutions.
- Integrates Generative AI within the ML Platform using state-of-the-art techniques.
Required qualifications, capabilities, and skills:
- MS and/or PhD in Computer Science, Machine Learning, or a related field, with applied machine learning experience.
- Experience in one of the programming languages like Python, Java, C/C++, etc. Intermediate Python is a must.
- Experience in applying data science, ML techniques to solve business problems.
- Solid background in Natural Language Processing (NLP) and Large Language Models (LLMs).
- Hands-on experience with machine learning and deep learning methods.
- Deep understanding and expertise in deep learning frameworks such as PyTorch or TensorFlow.
- Experience in advanced applied ML areas such as GPU optimization, fine-tuning, embedding models, inferencing, prompt engineering, evaluation, RAG (Similarity Search).
- Ability to work on tasks and projects through to completion with limited supervision.
- Passion for detail and follow-through.
- Excellent communication skills and team player.
Preferred qualifications, capabilities, and skills:
- Master's degree in computer science, ML or related areas.
- Experience with Ray, MLFlow, and/or other distributed training frameworks.
- In-depth understanding of Search/Ranking, Recommender systems, Graph techniques, and other advanced methodologies.
- Deep understanding of Large Language Model (LLM) techniques, including Agents, Planning, Reasoning, and other related methods.
- Experience with building and deploying ML models on cloud platforms such as AWS and AWS tools like Sagemaker, EKS, etc.
- Experience working with large-scale MLOps pipelines, working with and deploying models to production services.
J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs.
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.
Lead Software Engineer - Agentic AI development | Bournemouth, UK employer: JPMorgan Chase & Co.
Contact Detail:
JPMorgan Chase & Co. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Software Engineer - Agentic AI development | Bournemouth, UK
✨Tip Number 1
Familiarise yourself with the latest advancements in machine learning and AI, particularly focusing on large language models (LLMs) and their applications. This knowledge will not only help you during interviews but also demonstrate your passion for the field.
✨Tip Number 2
Engage with the AI and machine learning community by attending relevant meetups, webinars, or conferences. Networking with professionals in the industry can provide valuable insights and potentially lead to referrals for the position.
✨Tip Number 3
Showcase your hands-on experience with Python and deep learning frameworks like PyTorch or TensorFlow through personal projects or contributions to open-source initiatives. This practical experience can set you apart from other candidates.
✨Tip Number 4
Prepare to discuss specific examples of how you've applied machine learning techniques to solve real-world problems. Being able to articulate your thought process and the impact of your work will impress interviewers and highlight your expertise.
We think you need these skills to ace Lead Software Engineer - Agentic AI development | Bournemouth, UK
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, AI, and software engineering. Emphasise your proficiency in Python and any hands-on experience with ML frameworks like PyTorch or TensorFlow.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and machine learning. Discuss specific projects where you've applied ML techniques and how they relate to the responsibilities outlined in the job description.
Showcase Your Technical Skills: Include a section in your application that details your technical skills, particularly in ML algorithms, NLP, and large language models. Mention any experience with cloud platforms like AWS and tools such as Sagemaker.
Highlight Collaboration Experience: Since the role involves working with product and engineering teams, provide examples of past collaborations. Describe how you contributed to team projects and the impact of your work on achieving project goals.
How to prepare for a job interview at JPMorgan Chase & Co.
✨Showcase Your Technical Expertise
As a Lead Software Engineer, it's crucial to demonstrate your in-depth knowledge of machine learning techniques and frameworks. Be prepared to discuss specific projects where you've applied ML algorithms, especially in Python, and how you optimised workflows using large language models.
✨Prepare for Problem-Solving Questions
Expect to face technical challenges during the interview. Brush up on your problem-solving skills, particularly in areas like Natural Language Processing and deep learning methods. Practice coding problems that require you to optimise algorithms or troubleshoot inefficiencies.
✨Emphasise Collaboration Skills
Collaboration is key in this role. Be ready to share examples of how you've worked with cross-functional teams to deliver technology-driven solutions. Highlight your communication skills and ability to work independently while still being a team player.
✨Demonstrate Passion for AI Innovation
Show your enthusiasm for cutting-edge AI technologies and their applications in software engineering. Discuss any personal projects or research you've undertaken in generative AI or model-driven engineering, as this will reflect your commitment to staying ahead in the field.